Sökning: "Range estimation"
Visar resultat 1 - 5 av 316 avhandlingar innehållade orden Range estimation.
1. Channel Estimation and Prediction for 5G Applications
Sammanfattning : Accurate channel state information (CSI) is important for many candidate techniques of future wireless communication systems. However, acquiring CSI can sometimes be difficult, especially if the user equipment is mobile in which case the future channel realisations must be estimated/predicted. LÄS MER
2. On motion resistance estimation and modeling for heterogeneous road vehicles
Sammanfattning : Climate change is driving the development of CO2 reducing technologies within the transportation industry. One of the most promising technologies is battery electric vehicles. LÄS MER
3. Automation of front-end loaders : electronic self leveling and payload estimation
Sammanfattning : A growing population is driving automatization in agricultural industry to strive for more productive arable land. Being part of this process, this work is aimed to investigate the possibility to implement sensor-based automation in a particular system called Front End Loader, which is a lifting arms that is commonly mounted on the front of a tractor. LÄS MER
4. Estimation Using Low Rank Signal Models
Sammanfattning : Designing estimators based on low rank signal models is a common practice in signal processing. Some of these estimators are designed to use a single low rank snapshot vector, while others employ multiple snapshots. This dissertation deals with both these cases in different contexts. LÄS MER
5. Nonparametric Functional Estimation under Order Restrictions
Sammanfattning : This thesis consists of three papers (Papers A-C) on problems in nonparametric functional estimation, in particular density and regression function estimation and deconvolution, under order assumptions. Pointwise limit distribution results are stated for the obtained estimators, which include isotonic regression estimates, nonparametric maximum likelihood estimates of monotone densities, estimates of convex regression and density functions and deconvolution estimates. LÄS MER